PUB 540 Calculating Odds Ratio

Sample Answer

From the above odds ratio, there is a public health importance for the association (Persoskie & Ferrer, 2017). In other words, the relationship determined can be applied in the determination of the negative consequences of binge drinking (Kilander et al., 2016). Determination of odds ratios is essential when it comes to the measurement of the association between exposure and non-exposure (Martinez et al., 2017).

In the above case, the odds ratio can be applied in the determination of the probability of depression occurring for the individuals engaged in the binge drinking (Meeks et al., 2016). From the previous case, the depression may also occur when an individual is not exposed to binge drinking.

Behavioral Risk Factor Surveillance System (BRFSS)

Calculated variable for binge drinkers, men having 5+ drinks on one occasion and women having 4+ drinks on one occasion (_RFBING5)

Statistics	Yes	No	Total
Total Sample Size	1406	5991	7397
Row %	19.2%	80.8%	100%
Column %		100%	100%
No Sample Size	1275	5441	6716
Row %	19.3%	80.7%	100%
Column %	86%	85.7%	85.8%
Total % (Weighted)	16.5%	69.2%	85.8%
Yes Sample Size	131	550	681
Row %	18.9%	81.1%	100%
Column %	14%	14.3%	14.2%
Total % (Weighted)	2.7%	11.6%	14.2%

 

• Wald Chi-Square Value: 0.03
• Degrees of Freedom: 1
• p-value: 0.8553
• Number of records on the BRFSS dataset for the year and location selected: 7946
• Number of records excluded from the analysis: 549
• Sample Size (Number of records used in the analysis): 7397
• Total Weighted N (Population): 4824701

(Stare & Maucort-Boulch, 2016)

Part I

The tables show the outcomes for the cross-tabulation between binge drinkers, men having 5+ drinks on one occasion and women having 4+ drinks on one occasion and depression.

For non-binge drinkers, odds ratio is given by:

• = p (1-p) (probability of non-drinkers binge having depression)
• = 19.3/80.7
• = 0.239

For binge drinkers, odds ratios is given by:

• = p (1-p) (probability of binge drinkers having depression)
• = 18.9/81.1
• = 0.233

In general, the odds ratio is given by:

• = p (1-p) (probability of binge drinkers having depression)/ p (1-p) (probability of binge drinkers having depression) (Hancock & Kent, 2016)
• = 0.239/0.233
• = 1.03

The odds show that individuals exposed to binge drinking are 1.03 times more likely to develop depression. In other words, those exposed to binge drinking are 3% more likely to have depression. The odds ratio is therefore a good estimate of the relative risk in this case

Part II

Calculated variable for 4 level smoker status everyday/someday/former/non-smoker (_SMOKER3) Calculated variable for ever told you had any types of cancer including skin cancer (CHCOCNCR, CHCSCNCR )

Statistics	Yes	No	Total
Total Sample Size	1773	5799	7572
Row %	13.7%	86.3%	100%
Column %		100%	100%
Total % (Weighted)	13.7%	86.3%	100%
Current smoker – every day Sample Size	47	223	270
Row %	11.9%	88.1%	100%
Column %	4.1%	4.9%	4.8%
Total % (Weighted)	0.6%	4.2%	4.8%
Former smoker Sample Size	740	1673	2413
Row %	21%	79%	100%
Column %	38.3%	22.9%	25%
Total % (Weighted)	5.2%	19.7%	25%
Never smoked Sample Size	876	3400	4276
Row %	10.9%	89.1%	100%
Column %	48.6%	63%	61%
Total % (Weighted)	6.7%	54.3%	61%

 

• Wald Chi-Square Value: 84.59
• Degrees of Freedom: 3
• p-value: <0.0001

 

• Number of records on the BRFSS dataset for the year and location selected: 7946
• Number of records excluded from the analysis: 374
• Sample Size (Number of records used in the analysis): 7572
• Total Weighted N (Population): 4950718

The table above shows the cross tabulation for smokers and the possibility of developing any form of cancer.

For everyday smokers, the odds ratio for developing any form of cancer is given by:

• = p (1-p) (every day smoker having any form of cancer) (Chang & Hoaglin, 2017)
• = 11.9/88.1
• = 0.134

For Current smoker – some days,

• = p (1-p) (some day smoker having any form of cancer)
• = 21/79
• = 0.27

Therefore, odds ratio is given by 0.27/0.134

• = 2.01

The above scenario shows that everyday smokers are two times more likely to develop any form of cancer including skin cancer (Katz, 2016). The public importance of the above association is that it can enhance the creation of awareness for smoking relate cancers. It can also be used in the processes of developing interventions for different types of cancers (Solmi et al., 2016).

In conclusion, there is the representation of cross-tabulation for the depression among the individuals exposed to binge drinking (Roman-Viñas et al., 2016). Odds ratios of an event occurring is defined as the probability or the likelihood that an event will occur, expresses as a percentage or as a proportion that the event will not occur (Persoskie & Ferrer, 2017).

References

• Chang, B. H., & Hoaglin, D. C. (2017). Meta-analysis of odds ratios current good practices. Medical care, 55(4), 328. 10.1097/MLR.0000000000000696
• Hancock, M., & Kent, P. (2016). Interpretation of dichotomous outcomes risk, odds, risk ratios, odds ratios and number needed to treat. Retrieved from www.elsevier.com/locate/jphys
• Katz, K. A. (2016). The (relative) risks of using odds ratios. Archives of dermatology, 142(6), 761-764. Retrieved from https //jamanetwork.com/journals/jamadermatology/article-abstract/405502
• Kilander, H., Alehagen, S., Svedlund, L., Westlund, K., Thor, J., & Brynhildsen, J. (2016). Likelihood of repeat abortion in a Swedish cohort according to the choice of post‐abortion contraception a longitudinal study. Acta obstetricia et gynecologica Scandinavica, 95(5), 565-571. Retrieved from https //obgyn.onlinelibrary.wiley.com/doi/full/10.1111/aogs.12874
• Martinez, B. A. F., Leotti, V. B., Nunes, L. N., Machado, G., & Corbellini, L. G. (2017). Odds ratio or prevalence ratio? An overview of reported statistical methods and appropriateness of interpretations in cross-sectional studies with dichotomous outcomes in veterinary medicine. Frontiers in veterinary science, 4, 193. https //doi.org/10.3389/fvets.2017.00193
• Meeks, K. A., Freitas-Da-Silva, D., Adeyemo, A., Beune, E. J., Modesti, P. A., Stronks, K., … & Agyemang, C. (2016). Disparities in type 2 diabetes prevalence among ethnic minority groups resident in Europe a systematic review and meta-analysis. Internal and emergency medicine, 11(3), 327-340. Retrieved from https //link.springer.com/article/10.1007%2Fs11739-015-1302-9
• Persoskie, A., & Ferrer, R. A. (2017). A most odd ratio interpreting and describing odds ratios. American journal of preventive medicine, 52(2), 224-228. https //doi.org/10.1016/j.amepre.2016.07.030
• Roman-Viñas, B., Chaput, J. P., Katzmarzyk, P. T., Fogelholm, M., Lambert, E. V., Maher, C., … & Tremblay, M. S. (2016). Proportion of children meeting recommendations for 24-hour movement guidelines and associations with adiposity in a 12-country study. International journal of behavioral nutrition and physical activity, 13(1), 1-10. Retrieved from https //link.springer.com/article/10.1186/s12966-016-0449-8
• Solmi, M., Veronese, N., Sergi, G., Luchini, C., Favaro, A., Santonastaso, P., … & Stubbs, B. (2016). The association between smoking prevalence and eating disorders A systematic review and meta‐analysis. Addiction, 111(11), 1914-1922. https //doi.org/10.1111/add.13457
• Stare, J., & Maucort-Boulch, D. (2016). Odds ratio, hazard ratio and relative risk. Metodoloski zvezki, 13(1), 59. Retrieved from https //ibmi.mf.uni-lj.si/mz/2016/no-1/p4.pdf